12.1. PeakPerformance

import numpy as np
import matplotlib.pyplot as plt
from molass_data import SAMPLE1
from molass.DataObjects import SecSaxsData as SSD
ssd = SSD(SAMPLE1)
x, y = ssd.xr.get_icurve().get_xy()
fig, ax = plt.subplots()
ax.plot(x, y)
plt.show()

np.save("example.npy", np.array((x, y)))

import arviz as az
import pymc as pm
from pathlib import Path
from peak_performance import pipeline as pl, models, plots
timeseries = np.load(Path(r"example.npy"))

fig, ax = plt.subplots()
ax.scatter(timeseries[0], timeseries[1], marker="x", color="black")
ax.set(
    xlabel="time / h",
    ylabel="intensity / a.u.",
)
plt.show()

pmodel = models.define_model_double_normal(
    time=timeseries[0],
    intensity=timeseries[1]
)
pmodel.to_graphviz()